NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Brazil win Group C in the 2026 FIFA World Cup?
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A live, interactive instrument for dissecting a single binary position. Sweep the inputs and watch every indicator recompute — payoff geometry, Kelly growth, Bayesian posterior, KL divergence, cost waterfall, Monte-Carlo equity fan, forecast calibration. Companion to the live /feed/pm-will-brazil-win-group-c-in-the-2026-fifa-world-cup page.
▲ YES EDGE · +0.013 · f★ 3.8% · deploy 1.9% · net 0.52pp
§1 · Position economics
YES · Expected P/L per share +0.0127@ model P(YES) = 0.678
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.80% · g(f★) = 0.037%deploy 1.90% · g = 0.027%
g(f)f★ optimumdeployed fgrowth zone
Underbet leaves growth on the table; overbet destroys capital. The interior maximum is f★.
§2 · The trade ticket
YES @ 0.665 · EV +$9stake $475 · 1.90% of bankroll
Deployed stakestake
$475
1.90% of bankroll
Sharesunits
714
each pays $1 if YES
Max payoutwin
$714
gross, if win
Max profitwin
+$239
net of cost
Max losslose
-$475
binary settles to $0
Payout multiple×
×1.50
$1 → $1.50
Risk:RewardR:R
0.50 : 1
win $0.50 per $1
Expected P/LE[P/L]
+$9
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 67.8% | +$239 | +$162 |
| Resolves against (lose) | 32.2% | -$475 | -$153 |
| Expected value | 100.0% | — | +$9 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.3 pprelative edge +1.9%
Required win ratebreak-even
66.5%
price = implied probability
Model win rateP(win)
67.8%
what you forecast
Cushionedge
+1.3 pp
margin of safety
Fair pricemodel
0.678
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
66.5%
= price
Decimal oddsEU
1.504
total return per $1
AmericanUS
-199
risk $199 to win $100
FractionalUK
0.50 / 1
profit per $1 risked
Profit per $100stake
+$50.38
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 33% · APY 39%ROI 1.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+1.9%
APR (simple)scaled
+33%
ROI × 365/days
APY (compounded)if redeployed
+39%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.09%
geometric, per day held
Capital turns/yrvelocity
×17.4
how often this slot recycles
simple APRcompounded APYyour horizon
Rank positions by APR, not raw ROI. A thin edge tomorrow beats a fat edge next year.
§5 · Costs & net edge
Net edge +0.52 pperosion 59% · break-even w/ fees 67.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$950
3.80% · g = 0.037%
Half Kelly½ f★
$475
1.90% · g = 0.027%
Quarter Kelly¼ f★
$237
0.95% · g = 0.016%
Flat 1%1%
$250
1.00% · g = 0.017%
Flat 2%2%
$500
2.00% · g = 0.028%
Flat 5%5%
$1,250
5.00% · g = 0.033%
Recommended¼ f★
$237
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.920 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.907 bit
Δ -0.013 bit vs market
Surprise · YES−log₂ p
0.59 bit
self-information
Surprise · NO−log₂(1−p)
1.58 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0004 nat (0.0005 bit)belief ≈ market — stand down
YES contributionNO contributionbelief ‖ marketnoise
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.678 · CI [0.56, 0.79] · κ 59.7
Posterior meanE[θ]
0.678
Beta(40.4, 19.2)
95% credible intervalHDI
[0.56, 0.79]
price INSIDE → weak edge
Concentrationκ
59.7
pseudo-obs behind belief
Disagreementvs crowd
+1.3 pp
posterior − price
market prior (dashed)model posterior95% credible bandmarket price
When the market price falls outside the 95% credible interval, your disagreement is statistically meaningful.
§9 · Tail risk · Monte-Carlo (mode A · single position to resolution)
E[P/L] -0.8% · P(YES) 66.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-0.75%
P(YES) empiricalq
66.0%
Best pathmax
+50.4%
Worst pathmin
-100.0%
VaR 95%5%
100.0%
CVaR 95%ES
100.0%
median path25/75 + 5/95 bandsentry pricemodel q
Logit-space mean-reverting walk + terminal flip with probability q. Answers: 'what happens to THIS one position'. Distinct from the repeated-edge fan below.
§9b · Tail risk · Monte-Carlo (mode B · repeated independent edges)
Median CAGR/bet 0.02% · ruin rate 0.0%400 paths × 120 bets · f deploy 1.90%
Sharpe / betμ/σ
0.033
μ 0.04% · σ 1.3%
Sortino / betμ/σ↓
0.023
downside-only denominator
VaR 95%5%
-1.9%
per-bet worst-case
CVaR 95%ES
-1.9%
mean tail loss
Max drawdownMDD
-2.9%
Calmar 0.01
Ruin rate≤50%
0.0%
P(equity ever ≤ 50%)
median25/75 band5/95 bandruin line
Answers a different question: 'if I could find this exact edge forever, what is the bankroll trajectory'. Compounds 120 sequential resolutions which is NOT what happens to a single position.
§10 · Base-rate & macro context
ANCHORED · supported by convictionanchor gap +19.6pp · crowd gap +18.3pp
Anchor gapmodel − base
+19.6 pp
Crowd gapprice − base
+18.3 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 15.7% · AUC 0.747out-of-sample BSS (5-fold) 15.7% ± 2.0% · Brier 0.2100 · log-loss 0.6266 · n 1600✓ n = 1600
BrierBS
0.2100
lower = better · ō 0.53
BSSvs base
15.7%
improvement over base rate
ReliabilityREL
0.0087
miscalibration · want ↓
ResolutionRES
0.0469
decisiveness · want ↑
Log lossLL
0.6266
cross-entropy
AUCROC
0.747
0.5 coin · 1.0 oracle
calibration curveROCUNC (irreducible)RES (skill, ↑)REL (miscalib, ↓)
Computed on a seeded synthetic forecast ledger. Reseed (⟳) to redraw.
§12 · Journal vitals (synthetic ledger)
BLEEDING · PF 0.85 · expectancy -0.081R180 trades · win 47.2% · Sharpe -0.078
Total P/Lnet
-$3,635
on $45,000 cycled
Win ratehit %
47.2%
85 W / 95 L
Profit factorPF
0.85
$ won / $ lost
Expectancyper trade
-$20.20
avg $ per position
R-expectancyper risk
-0.081R
in units of risk taken
Avg win / losspayoff
$236.64 / -$250.00
ratio 0.95 : 1
Sharpe / traderisk-adj
-0.078
μR / σR
Closing line valueCLV
+2.31 pp
avg edge vs close
cumulative P/Lprofitable zonered zonesynthetic · seeded from asset
The scorecard every trader checks. Synthetic ledger seeded from the asset slug — recomputes against your real fill history once wired.